
Tech Lead
- Bangalore, Karnataka
- Permanent
- Full-time
- Architect and own the full AI stack, including LLM hosting, backend services, orchestration, and infrastructure.
- Design and optimize multi-agent orchestration pipelines with contextual memory and intelligent handoff mechanisms.
- Deploy, fine-tune, and optimize LLMs using self-hosted and open-source frameworks (e.g., Ollama, HuggingFace, LangChain).
- Implement secure, private AI pipelines with role-based access, encryption, and monitoring — ensuring sensitive data never leaves the environment.
- Make strategic infrastructure choices (GPU clusters, vector databases, orchestration tools) to balance performance, cost, and security.
- Lead DevOps practices such as CI/CD, observability, monitoring, and auto-scaling for AI workloads.
- Mentor and guide engineering teams on best practices for model deployment, scaling, and optimization.
- Collaborate with Product and Design teams to accelerate feature delivery and improve cross-functional outcomes.
- Ensure compliance with data protection regulations (GDPR, privacy-first AI design).
- Continuously evaluate emerging OSS models and frameworks to improve cost-efficiency and system performance.
- 7+ years of experience in software engineering/AI systems, with at least 3+ years in ML/LLM deployment.
- Strong background in LLM hosting and fine-tuning (Ollama, HuggingFace, LangChain, vLLM, LoRA).
- Proven experience deploying generative AI across multiple modalities (text, image, video).
- Expertise in GPU infrastructure across cloud (AWS/GCP/Azure) and hybrid/on-prem setups, with Kubernetes/Docker.
- Solid backend engineering skills (Python, FastAPI/Node.js, microservices, event-driven systems).
- Track record of leading engineering teams and delivering production-grade AI products.
- Strong knowledge of vector databases (Pinecone, Weaviate, Milvus) and retrieval pipelines (RAG).
- Excellent communication skills to align product, design, and technical teams.
- Experience with multi-agent or Agentic AI systems.
- Background in marketing-tech or SaaS product platforms.
- Knowledge of GPU optimization techniques (quantization, batching, caching).
- Hands-on experience with privacy-first AI architectures.
- LLM Deployment
- AI Systems Architecture
- Multi-Agent Orchestration
- Secure AI Infrastructure